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Record W2101054552 · doi:10.1146/annurev.nutr.21.1.297

G<scp>ASTROINTESTINAL</scp>N<scp>EMATODES</scp>, N<scp>UTRITION AND</scp>I<scp>MMUNITY</scp>: Breaking the Negative Spiral

2001· review· en· W2101054552 on OpenAlexaff
Kristine G. Koski, Marilyn E. Scott

Bibliographic record

VenueAnnual Review of Nutrition · 2001
Typereview
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyMalnutritionImmune systemNematodeImmunologyHost (biology)Vitamin D and neurologyInternal medicineMedicineEndocrinologyEcology

Abstract

fetched live from OpenAlex

Nutritionists have long understood that intestinal nematode parasites have deleterious effects on host nutritional status, but only recently has the importance of malnutrition as a predisposing factor to intestinal nematodes been recognized. Here we review experimental and field studies on the effects of protein, energy, zinc, vitamin A, and iron deficiencies on gastrointestinal (GI) nematodes of humans, livestock, and laboratory rodents, and draw certain conclusions about the state of our current understanding. In general, malnutrition promotes the establishment, survival, and fecundity of these parasites, but the magnitude of the effect depends on factors such as host species, parasite species, particular infection protocol used, magnitude of the infection, severity of the nutritional deficiency, and presence of single or multiple infections and single or multiple nutritional deficiencies. We highlight the Th2 arm of the immune system as a component of primary importance in the association between malnutrition and GI nematode infections. We summarize what is known about underlying mechanisms that may account for the observed patterns. Finally, we suggest future research directions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.341
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations188
Published2001
Admission routes1
Has abstractyes

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